Lexplorer: Navigating the Complexity of Legal Document Landscapes
- URL: http://arxiv.org/abs/2609.17366v1
- Date: Tue, 15 Sep 2026 16:04:06 GMT
- Title: Lexplorer: Navigating the Complexity of Legal Document Landscapes
- Abstract summary: We propose Lexplorer, a flexible interface for exploring, navigating, and analyzing legal documents, based on a taxonomy capturing user intents.<n>We evaluate Lexplorer in the context of European Union law, taxonomy, intent, and prototype design.<n>Resulting from a close collaboration between visual-analytics researchers and legal scholars, our work also provides nuanced insights into the process required to design interactive systems.
- Score: 4.351505522514463
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: As technological and social innovations create novel regulatory challenges, legal systems grow in complexity - increasing the need for interfaces that enable effective interactions with legal document collections. Through interviews with legal scholars (n=15), we find that supporting legal work requires going beyond retrieval-centered legal-information-system paradigms. Hence, we propose Lexplorer, a flexible interface for exploring, navigating, and analyzing legal documents, based on a taxonomy capturing user intents. Distinguishing text and data views for one, few, and many documents, Lexplorer enables context-sensitive interactions with evolving collections of interconnected legal texts, facilitating Adaptive Meaning Construction in law. We evaluate Lexplorer with legal scholars (n=20) in the context of European Union law, validating our elicited requirements, intent taxonomy, and prototype design. Resulting from a close collaboration between visual-analytics researchers and legal scholars, our work also provides nuanced insights into the process required to design interactive systems for expert domains driven by implicit methodological knowledge.
Related papers
- WisdomInterrogatory (LuWen): An Open-Source Legal Large Language Model Technical Report [55.27414605169639]
We present WisdomInterrogatory (LuWen), an open-source Chinese legal language model built upon the Baichuan foundation model.<n>We evaluate LuWen on five representative legal tasks spanning both prediction and generation settings.
arXiv Detail & Related papers (2026-04-08T06:59:07Z) - AI-Powered Legal Intelligence System Architecture: A Comprehensive Framework for Automated Legal Consultation and Analysis [0.0]
The LICES architecture can reduce preliminary legal research and case assessment time by more than 90% compared to traditional paralegal benchmarks.<n>Performance evaluations indicate that the LICES architecture can reduce preliminary legal research and case assessment time by more than 98%.
arXiv Detail & Related papers (2025-08-24T19:41:26Z) - Bridging Legal Knowledge and AI: Retrieval-Augmented Generation with Vector Stores, Knowledge Graphs, and Hierarchical Non-negative Matrix Factorization [6.0045906216050815]
Agentic Generative AI, powered by Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG), Knowledge Graphs (KGs), and Vector Stores (VSs)<n>This technology excels at inferring relationships within vast unstructured or semi-structured datasets.<n>We introduce a generative AI system that integrates RAG, VS, and KG, constructed via Non-Negative Matrix Factorization (NMF)
arXiv Detail & Related papers (2025-02-27T18:35:39Z) - Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges [7.767611860493713]
This survey follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, reviewing 154 studies, with a final selection of 131 after manual filtering.<n>It explores foundational concepts related to NLP in the legal domain, illustrating the unique aspects and challenges of processing legal texts.<n>We provide an overview of NLP tasks specific to legal text, such as Document Summarisation, Named Entity Recognition, Question Answering, Argument Mining, Text Classification, and Judgement Prediction.
arXiv Detail & Related papers (2024-10-25T01:17:02Z) - InternLM-Law: An Open Source Chinese Legal Large Language Model [72.2589401309848]
InternLM-Law is a specialized LLM tailored for addressing diverse legal queries related to Chinese laws.
We meticulously construct a dataset in the Chinese legal domain, encompassing over 1 million queries.
InternLM-Law achieves the highest average performance on LawBench, outperforming state-of-the-art models, including GPT-4, on 13 out of 20 subtasks.
arXiv Detail & Related papers (2024-06-21T06:19:03Z) - Enhancing Pre-Trained Language Models with Sentence Position Embeddings
for Rhetorical Roles Recognition in Legal Opinions [0.16385815610837165]
The size of legal opinions continues to grow, making it increasingly challenging to develop a model that can accurately predict the rhetorical roles of legal opinions.
We propose a novel model architecture for automatically predicting rhetorical roles using pre-trained language models (PLMs) enhanced with knowledge of sentence position information.
Based on an annotated corpus from the LegalEval@SemEval2023 competition, we demonstrate that our approach requires fewer parameters, resulting in lower computational costs.
arXiv Detail & Related papers (2023-10-08T20:33:55Z) - Constructing a Knowledge Graph for Vietnamese Legal Cases with
Heterogeneous Graphs [5.168558598888541]
This paper presents a knowledge graph construction method for legal case documents and related laws.
Our approach consists of three main steps: data crawling, information extraction, and knowledge graph deployment.
arXiv Detail & Related papers (2023-09-16T18:31:47Z) - SAILER: Structure-aware Pre-trained Language Model for Legal Case
Retrieval [75.05173891207214]
Legal case retrieval plays a core role in the intelligent legal system.
Most existing language models have difficulty understanding the long-distance dependencies between different structures.
We propose a new Structure-Aware pre-traIned language model for LEgal case Retrieval.
arXiv Detail & Related papers (2023-04-22T10:47:01Z) - Entity Graph Extraction from Legal Acts -- a Prototype for a Use Case in
Policy Design Analysis [52.77024349608834]
This paper presents a prototype developed to serve the quantitative study of public policy design.
Our system aims to automate the process of gathering legal documents, annotating them with Institutional Grammar, and using hypergraphs to analyse inter-relations between crucial entities.
arXiv Detail & Related papers (2022-09-02T10:57:47Z) - iFacetSum: Coreference-based Interactive Faceted Summarization for
Multi-Document Exploration [63.272359227081836]
iFacetSum integrates interactive summarization together with faceted search.
Fine-grained facets are automatically produced based on cross-document coreference pipelines.
arXiv Detail & Related papers (2021-09-23T20:01:11Z) - Explaining Relationships Between Scientific Documents [55.23390424044378]
We address the task of explaining relationships between two scientific documents using natural language text.
In this paper we establish a dataset of 622K examples from 154K documents.
arXiv Detail & Related papers (2020-02-02T03:54:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.